Tools Are the Building Blocks of Innovation – But You Still Need to Consider What You’re Building

“Your scientists were so preoccupied with whether or not they could, they didn’t stop to think if they should.” Ian Malcolm in Jurassic Park

I think the truth about AI lies somewhere between “savior of everything” and “doom for humanity”. There are things AI does much better than humans, such as processing huge amounts of information and finding patterns in the data. But it falls short on originality, empathy, and even in understanding humor (among other things).

Before bringing in a new powerful tool, everyone committed to implementing this tool should know the answers to the following questions:

1. What does this tool do?
2. How will this tool make our organization more efficient or profitable?
3. How difficult will this tool be to implement?
4. Who will this tool impact within the organization, and how?
5. Can we support this tool?
6. What results can we expect?

Transformational technology must start with a firm grasp of the “Why?” and the value of the effort to the organization. Only then can you move to the “How?”. 

For comparison, consider another tool—enterprise resource planning (ERP) software. Some ERP projects have had spectacular (and expensive) failures (see here and here). Lessons learned from those can apply to other technologies such as AI. Many of the causes for the failures aren’t technical, but organizational or managerial, such as:

• Flimsy system requirements, Insufficient understanding of system and business requirements
• Fluctuating budgets, Lack of funding and resources

• Lack of leadership buy-in
• Poor employee training
• Too many project leaders/cooks in the kitchen
• Inadequate change control

In fact, these are issues that arise on many different kinds of projects.

At a high level, an AI project is no different from other projects. Yes, the technology involved is different, and it brings a unique set of challenges. But from a business perspective, AI is just another tool. If your organization has a framework for project success, it should be followed for an AI project the same as any other type of project.

Before embarking on an AI project, ensure that the foundation is in place. This should include:

• A business case with specific, measurable outcomes
• A firm grasp on business and system requirements
• Stakeholder support
• Adequate resources and necessary technical expertise
• Financial support

While AI can certainly be a game-changer, it is certainly NOT all rainbows and unicorns. It’s time to ignore the hype, recognize opportunities, and proceed rationally.

Melissa Swartz is writing on behalf of the SCTC, a premier professional organization for independent consultants. Our consultant members are leaders in the industry, able to provide best of breed professional services in a wide array of technologies. Every consultant member commits annually to a strict Code of Ethics, ensuring they work for the client benefit only and do not receive financial compensation from vendors and service providers.